
Poor coherence in sequence of text or across multiple turns of generated conversation [1]}, [2]}.

Lack of utterance diversity [3]}.

Bland repetitive utterances [3]}, [5]}.

Lack of empathetic responses from conversational systems [6]}.

Lack of memory to personalise user experiences.

Style inconsistency or lack of persona [7]}, [5]}.

Multiple initiative coordination [1]}.

Poor inference and implicature during conversation.

Lack of world-knowledge.

Poor adaptation or responses to idioms or figurative language [10]}

Hallucination of facts when generating responses [11]}.

Obsolete facts, which are frozen in the models' weights during at training .

Training requires a large amount of data [11]}.

Lack of common-sense reasoning [11]}.

Large models use so many parameters that make them complex and may impede transparency [11]}.

Lack of training data for low-resource languages [15]}, [16]}

